LSR1 analysis: Pro-dopaminergic pharmacological interventions for anhedonia in depression
Francesca Tinsdeall, Fiona Ramage, Virginia Chiocchia and Malcolm Macleod
09 February 2024
- 1. Flow of study selection and descriptives
- 2 Effects of model induction
- 3 Dopaminergic agent v Control
- 4. Observed relationships between different outcomes measures in the same cohorts of animals
- 5. Attrition bias and adverse effects of treatment
- 6. Summary of the evidence
- 7. Software used
1. Flow of study selection and descriptives
The flow of study selection is shown in Figure 1. Studies included were published between 1992 and 2023. Overall, this analysis includes 26 studies containing 323 comparisons.
Figure 1
Table 1 below gives a summary of the included studies for the effect of model induction. N represents an aggregate of animals contributing to outcomes reported from control and treatment groups, and if the same control group has contributed to more than one experiment, those animals will be counted more than once.
| Study | Model | Strain | Outcome | N |
|---|---|---|---|---|
| AMIRI, 2016 | maternal separation | NMRI | Sucrose preference test | 24 |
| BORGES, 2013 | iuGC | Wistar (rat) | DOPAC concentration | 20 |
| ~ | ~ | ~ | Dopamine concentration | 20 |
| ~ | ~ | ~ | Sucrose preference test | 14 |
| BROCCO, 2006 | CMS | Wistar (rat) | Sucrose preference test | 288 |
| CARRATAL, 2023 | Tetrabenzine | CD-1 (mouse) | Sucrose preference test | 132 |
| EREN, 2007 | CMS | Wistar (rat) | Sucrose preference test | 80 |
| EREN, 2014 | CUMS | Wistar (rat) | Sucrose preference test | 64 |
| FATIMA, 2020 | PNS | Wistar (rat) | Dopamine receptor biology | 24 |
| ~ | ~ | ~ | Sucrose preference test | 12 |
| JIANG, 2014 | Defeat | C57BL/6J (mouse) | Sucrose preference test | 100 |
| KOO, 2018 | MCAO | C57BL/6 (mouse) | Sucrose preference test | 36 |
| KRUPINA, 1995 | MPTP | Wistar (rat) | Sucrose preference test | 480 |
| MUSCAT, 1992 | CMS | Lister hooded (rat) | Sucrose preference test | 40 |
| OSACKA, 2022 | CMS | Sprague-dawley (rat) | Sucrose preference test | 21 |
| PAPP, 1993 | CUMS | Lister hooded (rat) | Sucrose preference test | 128 |
| QIAO, 2020 | CUS | Sprague-dawley (rat) | Dopamine concentration | 24 |
| ~ | ~ | ~ | Dopamine receptor biology | 24 |
| ~ | ~ | ~ | Sucrose preference test | 24 |
| RANA, 2014 | CMS | Swiss albino | Sucrose preference test | 60 |
| TAN, 2015 | TBI | Sprague-dawley (rat) | DOPAC concentration | 120 |
| ~ | ~ | ~ | Dopamine concentration | 120 |
| ~ | ~ | ~ | Sucrose preference test | 60 |
| TOMAZ, 2020 | LPS | Wistar (rat) | Sucrose preference test | 16 |
| WANG, 2021 | CUS | C57BL/6 (mouse) | Sucrose preference test | 16 |
| WEI, 2021 | CMS | C57BL/6J (mouse) | Sucrose preference test | 12 |
| WILLNER, 1994 | CUMS | PVG Hooded | Sucrose preference test | 44 |
| WU, 2014 | CUMS | Sprague-dawley (rat) | Sucrose preference test | 12 |
| YAN, 2022 | CUMS | Sprague-dawley (rat) | DA/DOPC ratio | 60 |
| ~ | ~ | ~ | Dopamine concentration | 60 |
| ~ | ~ | ~ | Sucrose preference test | 20 |
| YU, 2016 | CUS | Wistar (rat) | Sucrose preference test | 48 |
| YUAN, 2011 | CUMS | Sprague-dawley (rat) | Sucrose preference test | 17 |
| ZHAO, 2018 | CMS | Sprague-dawley (rat) | Sucrose preference test | 60 |
Glossary
iuGC - intra-uterine glucocorticoid: CMS - chronic mild stress: CUMS - chronic unpredictable mild stress: CUS - chronic unpredicatble stress: PNS - prenatal stress: Defeat - social defeat stress: TBI - traumatic brain injury: LPS - intraperitoneal lipopolysaccharide: MCAO - middle cerebral artery occlusion: WAG/Rij = genetic model of absence epilepsy with co-morbid depression
Table 2 below gives a summary of the included studies for the effect of doapminergic interventions. N represents an aggregate of animals contributing to outcomes reported from control and treatment groups, and if the same control group has contributed to more than one experiment, it will be counted twice.While some authors considered imipramine to have dopaminergic effects, we considered, given that this was a minor contribution to its pharmacological repertoire, that these studies should not be included in this iteration of the review.
| Study | Model | Strain | Comparison | Outcome | N |
|---|---|---|---|---|---|
| AMIRI, 2016 | maternal separation | NMRI | selegiline, 1 mg/kg | Sucrose preference test | 12 |
| ~ | ~ | ~ | selegiline, 3 mg/kg | ~ | 24 |
| ~ | ~ | ~ | selegiline, 5 mg/kg | ~ | 12 |
| BORGES, 2013 | iuGR | Wistar (rat) | L-DOPA, 24 mg/kg | DOPAC concentration | 20 |
| ~ | ~ | ~ | ~ | Dopamine concentration | 20 |
| ~ | ~ | ~ | ~ | Sucrose preference test | 14 |
| BROCCO, 2006 | CMS | Wistar (rat) | piribedil, 10 mg/kg | Sucrose preference test | 96 |
| ~ | ~ | ~ | piribedil, 2.5 mg/kg | ~ | 96 |
| ~ | ~ | ~ | piribedil, 40 mg/kg | ~ | 96 |
| CARRATAL, 2023 | Tetrabenzine | CD-1 (mouse) | buproprion, 10 mg/kg | Sucrose preference test | 132 |
| EREN, 2007 | CMS | Wistar (rat) | aripiprazole, 2.5 mg/kg | Sucrose preference test | 80 |
| EREN, 2014 | CUMS | Wistar (rat) | aripiprazole, 2.5 mg/kg | Sucrose preference test | 64 |
| FATIMA, 2020 | PNS | Wistar (rat) | ropinirole, 10 mg/kg | Dopamine receptor biology | 24 |
| ~ | ~ | ~ | ~ | Sucrose preference test | 12 |
| JIANG, 2014 | Defeat | C57BL/6J (mouse) | SKF83959, 0.5 mg/kg | Sucrose preference test | 20 |
| ~ | ~ | ~ | SKF83959, 1 mg/kg | ~ | 100 |
| KOO, 2018 | MCAO | C57BL/6 (mouse) | aripiprazole, 1 mg/kg | Sucrose preference test | 36 |
| MUSCAT, 1992 | CMS | Lister hooded (rat) | quinpirole, 200 ug/kg | Sucrose preference test | 40 |
| OSACKA, 2022 | CMS | Sprague-dawley (rat) | aripiprazole, 10 mg/kg | Sucrose preference test | 22 |
| PAPP, 1993 | CUMS | Lister hooded (rat) | quinpirole, 100 ug/kg | Sucrose preference test | 96 |
| ~ | ~ | ~ | quinpirole, 200 ug/kg | ~ | 96 |
| ~ | ~ | ~ | quinpirole, 400 ug/kg | ~ | 96 |
| QIAO, 2020 | CUS | Sprague-dawley (rat) | dopamine, 3.83 ug | Sucrose preference test | 24 |
| ~ | ~ | ~ | quinpirole, 0.877 ug | ~ | 24 |
| RANA, 2014 | CMS | Swiss albino | L-DOPA, 200 mg/kg & simvastatin, 10 mg/kg | Sucrose preference test | 60 |
| ~ | ~ | ~ | bromocriptine, 2 mg/kg & simvastatin, 10 mg/kg | ~ | 60 |
| ~ | ~ | ~ | simvastatin, 10 mg/kg | ~ | 60 |
| RUSSO, 2013 | WAG/Rij rat | WAG/Rij | aripiprazole, 0.3 mg/kg | Sucrose preference test | 20 |
| ~ | ~ | ~ | aripiprazole, 1 mg/kg | ~ | 20 |
| ~ | ~ | ~ | aripiprazole, 3 mg/kg | ~ | 20 |
| TAN, 2015 | TBI | Sprague-dawley (rat) | amantadine, 45 mg/kg | DOPAC concentration | 112 |
| ~ | ~ | ~ | ~ | Dopamine concentration | 112 |
| ~ | ~ | ~ | ~ | Sucrose preference test | 56 |
| ~ | ~ | ~ | amantadine, 135 mg/kg | DOPAC concentration | 112 |
| ~ | ~ | ~ | ~ | Dopamine concentration | 112 |
| ~ | ~ | ~ | ~ | Sucrose preference test | 56 |
| TOMAZ, 2020 | LPS | Wistar (rat) | tranylcypromine, 10 mg/kg | Sucrose preference test | 16 |
| WANG, 2021 | CUS | C57BL/6 (mouse) | cryptotanshinone, 20 mg/kg | Sucrose preference test | 16 |
| WEI, 2021 | CMS | C57BL/6J (mouse) | pramipexole, 1 mg/kg | Sucrose preference test | 12 |
| WILLNER, 1994 | CUMS | PVG Hooded | pramipexole, 1 mg/kg | Sucrose preference test | 88 |
| ~ | ~ | ~ | pramipexole, 2 mg/kg | ~ | 88 |
| WU, 2014 | CUMS | Sprague-dawley (rat) | SKF38393, 1.12 ug | Sucrose preference test | 12 |
| YAN, 2022 | CUMS | Sprague-dawley (rat) | P. orientalis seed, 10 mg/kg | DA/DOPC ratio | 60 |
| ~ | ~ | ~ | ~ | Dopamine concentration | 60 |
| ~ | ~ | ~ | ~ | Sucrose preference test | 20 |
| ~ | ~ | ~ | P. orientalis seed, 33 mg/kg | DA/DOPC ratio | 60 |
| ~ | ~ | ~ | ~ | Dopamine concentration | 60 |
| ~ | ~ | ~ | ~ | Sucrose preference test | 20 |
| ~ | ~ | ~ | P. orientalis seed, 100 mg/kg | DA/DOPC ratio | 60 |
| ~ | ~ | ~ | ~ | Dopamine concentration | 60 |
| ~ | ~ | ~ | ~ | Sucrose preference test | 20 |
| YU, 2016 | CUS | Wistar (rat) | amantadine, 25 mg/kg | Sucrose preference test | 48 |
| YUAN, 2011 | CUMS | Sprague-dawley (rat) | SKF38393, 1.12 ug/kg | Sucrose preference test | 16 |
| ZHAO, 2018 | CMS | Sprague-dawley (rat) | 2_HBC, 10 mg/kg | Sucrose preference test | 60 |
| ~ | ~ | ~ | 2_HBC, 2.5 mg/kg | ~ | 60 |
| ~ | ~ | ~ | buproprion, 2.5 mg/kg | ~ | 60 |
References of included studies are located in the appendix. Included studies used 26 unique disease model induction procedures.
1.1 Description of experiment types and methodological approach
Within the literature we identified distinct categories of experiments and the data presented would allow several meta-analytical contrasts to be drawn:
Effects of diease modelling. These are experiments investigating the effect of models of depression, reported in 147 experiments from 25 publications.
In these studies the:
Control group is a group of animals that is (1) not subjected to a depression model induction paradigm and (2) is administered a control treatment (vehicle) or no treatment.
Intervention group is a group of animals that is (1) subjected to a depression model induction paradigm and (2) is administered a control treatment (vehicle) or no treatment.
Treatment vs control. These were experiments investigating the effect of administering a dopaminergic agent, reported in 176 experiments from 25 publications.
In these studies the:
Control group is a group of animals that is (1) subjected to a depression model induction paradigm and (2) administered a control treatment (vehicle) or no treatment.
Intervention group is a group of animals that is (1) subjected to a depression model induction paradigm and (2) administered a TAAR1 agonist treatment.
Sham group is a group of animals that is (1) not subjected to a depression model induction paradigm and (2) administered a control treatment (vehicle) or no treatment. These data are required to allow a ‘normalised mean difference’ effect size to be calculated, given by
\[ \frac{{\bar{\mu}_C - \bar{\mu}_T}}{{\bar{\mu}_C - \bar{\mu}_S}} \times 100 \]
where \(\bar{\mu}_C\), \(\bar{\mu}_T\), \(\bar{\mu}_S\) are the mean reported scores in the control, treatment, and sham groups respectively.
Outcomes with ≥2 independent effect sizes were considered for meta-analysis. In this iteration of the review, this includes sucrose preference test, dopamine concentration, dopac concentration and dopamine receptor biology.
All analyses were conducted allowing for the following hierarchical levels in a random effects model, which accounts for features common to experimental contrasts such as a shared control group:
Level 1: Rodent strain - effect sizes measured across experiments using the same rodent strain.
Level 2: Study - effect sizes measured from different experiments presented in the same publication.
Level 3: Experiment - effect sizes measured in the same experiment within a study, where often a control group contributes to several effect sizes.
Each level for the heirarchy was only included in the model if more than 4 categories were present for at least one of these levels. Where more than 4 categories are not present for all levels, the variance attributable to that level is reported as zero.
The hierarchical grouping may therefore be considered thus: Strains of laboratory animals are included in several Studies, each of which can report one or more Experiments, and each Experiment is comprised of at least two Cohorts which are considered identical except for differing in the experimental manipulation (the Intervention) or not being exposed to the disease modelling procedures (a Sham cohort, these only being used to provide a baseline for outcome measures to allow Normalised Mean Difference meta-analysis). An Experiment can include several experimental contrasts, for instance where different doses of drugs are compared to the same control group.
We constructed multilevel models without Knapp-Hartung adjustments as
these are not available for rma.mv class objects in the metafor package.
Instead, the model is set to test = "t" to use t- and
F-distributions for making inferences, and dfs="contain" to
improve the method of approximating degrees of freedom of these
distributions.
The scales and units used to measure outcomes in preclinical studies often differ between studies although they may measure the same underlying biological construct. The primary effect size used for meta-analysis of preclinical studies is therefore the standardised mean difference (SMD, Hedge’s g). For experiments testing the effects of interventions we also present a sensitivity analysis using normalised mean difference (NMD), where there are sufficient data for sham procedures to allow this. This analysis is not possible for studies of the effect of modelling depression.
For some experimental contrasts, more than one outcome of the same category - for instance dopamine concentrations in different brain regions - was measured in the same cohort of animals. Sometimes, sucrose preference tests were performed in the same cohort at different times. Some publications used the same drug doses with the same outcome measures in independent experiments. For these reasons, some of the forest plots may appear to include ‘duplicate’ Study - Drug - Dose combinations with different outcomes. For the later, these are accounted for in the hierarchical analysis, but for the former there were insufficient levels of the different outcome category measured to allow for hierarchical analysis and so this was not performed.
2 Effects of model induction
25 studies (147 comparisons) investigated the effects of model induction. The number of studies and individual effect sizes for each outcome were:
Sucrose preference*: 25 studies and 117 comparisons in 9 strains
Dopamine concentration: 4 studies and 14 comparisons in 2 strains
DOPAC concentration: 2 studies and 10 comparisons in 2 strains
DA/DOPAC ratio: 1 studies and 3 comparisons in 1 strain
Dopamine receptor biology: 2 studies and 3 comparisons in 2 strains
* This outcome was identified in the study protocol as the primary outcome of interest.
2.1 Outcome 1: Sucrose preference
2.1.1 Risks of bias
Figure 2.1.1 shows the risk of bias summary for studies investigating the effect of modelling depression on sucrose preference in animals. The risk of bias assessment was performed using the SyRCLE RoB tool.
Figure 2.1.1
2.1.2 Reporting completeness
Figure 2.1.2 shows the reporting completeness summary for studies investigating the effect of modelling depression on sucrose preference in animals. The reporting completeness assessment was performed using the ARRIVE guidelines.
Figure 2.1.2
2.1.3 Meta-analysis
The effect of modelling depression on sucrose preference in animals using SMD as the effect size is shown in Figure 2.1.3. The pooled estimate for SMD across all individual comparisons is displayed as a diamond shape at the bottom of the plot. Dotted lines indicate the prediction interval of the pooled estimate.
Figure 2.1.3
Depression modelling had a pooled effect on sucrose preference of SMD = -1.505 , (95% CI: -2.267 to -0.744 with a prediction interval of -4.423 to 1.412.
117 experimental comparisons were reported in 33 experiments reported from 25 publications and involving 9 different animal strains.
The following table structure is used throughout this report and is used to show the different levels contributing to that analysis, the number of unique categories in those levels, and the variance contributed by that level of analysis. Because levels are only included in the analysis where there are five or more unique categories, for some analyses the number of categories is 0, and the variance attributed to those levels in not applicable. Because the model is hierarchical, where for instance there are Studies which include different Strains, the number of categories for Study x Strain will exceed the number of Studies (by which we mean unique publications) referred to in the text.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 9 | 0.311 |
| Study x Strain | 25 | 1.17 |
| Study x Strain x Experiment | 33 | 0.01 |
2.1.4 Subgroup analyses and meta-regressions
For each outcome, the covariates of interest for subgroup analyses and meta-regressions were:
Sex
Method of disease induction
We also conducted subgroup analyses using (1) SyRCLE Risk of Bias and (2) ARRIVE reporting completeness assessment scores as covariates to evaluate their influence on effect size estimates. These were not specified in the study protocol, but evaluation of risk of bias is required for the Summary of Evidence table, and no studies were considered entirely at low risk of bias or of high reporting completeness to allow such a sensitivity analysis
The significance (p value) reported is that for a test of whether the moderators are significantly different one from another, rather than whether the effect is significantly different from 0.
Sex
Figure 2.1.4.1 displays the estimates for the pooled SMD’s when comparisons are stratified by sex of the animal. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by sex, is displayed as a diamond shape at the bottom of the plot.
Figure 2.1.4.1
The p-value for the association between the sex of animal groups used and outcome reported was 0.014.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 9 | 0.104 |
| Study x Strain | 25 | 0.828 |
| Study x Strain x Experiment | 33 | 0 |
Category of disease induction
Figure 2.1.4.2 displays the estimates for the pooled SMD’s when comparisons are stratified by the category of disease induction. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by category of disease induction, is displayed as a diamond shape at the bottom of the plot.
Figure 2.1.4.2
The p-value for the association between the depression model used and the outcome reported was 0.244.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 9 | 0.414 |
| Study x Strain | 25 | 1.129 |
| Study x Strain x Experiment | 33 | 0.007 |
SyRCLE RoB assessment considered as a categorical variable
Figure 2.1.4.3 displays the estimates for the pooled SMD’s when comparisons are stratified by how many of the SyRCLE risk of bias assessment criteria (of which there are 10) that the experiment met. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by SyRCLE Risk of Bias, is displayed as a diamond shape at the bottom of the plot.
Figure 2.1.4.3
The p-value for the association between SyRCLE Risks of Bias reporting and outcome reported was 0.12.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 9 | 0.274 |
| Study x Strain | 25 | 1.147 |
| Study x Strain x Experiment | 33 | 0.008 |
SyRCLE RoB assessment considering those studies where any item is at low risk of bias
Figure 2.1.4.4 displays the estimates for the pooled SMD’s when comparisons are stratified by whether of not any of the SyRCLE Risk of bias domains were rated as low risk of bias. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by SyRCLE Risk of Bias, is displayed as a diamond shape at the bottom of the plot.
Figure 2.1.4.4
The p-value for the association between low SyRCLE Risks of Bias reporting and outcome reported was 0.12.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 9 | 0.274 |
| Study x Strain | 25 | 1.147 |
| Study x Strain x Experiment | 33 | 0.008 |
ARRIVE reporting completeness guidelines
We provide a metaregression where the number of ARRIVE items met is considered as a continuous variable.
Figure 2.1.4.5
The p-value for the association between ARRIVE reporting completeness and outcome reported was 0.436).
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 9 | 0.373 |
| Study x Strain | 25 | 1.205 |
| Study x Strain x Experiment | 33 | 0.009 |
Heterogeneity explained by covariates (Effect of modelling on Sucrose preference)
The table below shows which of the covariates, if any, explain some of the heterogeneity observed in the effect sizes of the effect of TAAR1 agonists on Sucrose preference. We present marginal R2, which measures the proportion of variance explained by including moderators in the model (the % change in the between-studies variance when the covariate is included in the model, in other words the % of the heterogeneity explained by the variable). The co-efficients are derived form an RMA model fitted with an intercept (and so represent, for each category, the point estimate and 95% CIs of the effect in that category).
| Moderator | Category | \(\beta\) | 95% CI | Marginal R2 (%) |
|---|---|---|---|---|
| Overall effect | - | -1.505 | -2.267 to -0.744 | - |
| Sex | - | - | - | 13.1% |
| - | Female | -0.658 | -1.744 to 0.428 | - |
| - | Male | -1.449 | -1.966 to -0.932 | - |
| - | Not reported | -5.24 | -8.07 to -2.41 | - |
| Category of disease model induction | - | - | - | 26% |
| - | Behavioural early life stress | -1.458 | -5.677 to 2.761 | - |
| - | Chronic unpredictable mild stress | -1.284 | -2.12 to -0.447 | - |
| - | Pharmacological early life stress | -2.1 | -4.888 to 0.688 | |
| - | Pharmacological post weaning stress | -0.94 | -2.56 to 0.681 | |
| - | Social or social defeat stress | -1.659 | -4.235 to 0.917 | |
| - | Surgical models | -4.125 | -6.408 to -1.843 | |
| Risk of Bias | - | - | - | 9.7% |
| - | 0 criteria met | -1.252 | -1.993 to -0.511 | - |
| - | 1 criteria met | -2.12 | -3.144 to -1.096 | - |
| Reporting completeness | - | - | - | 2.7% |
| - | per unit increase | 0.118 | -0.189 to 0.424 | - |
2.1.5 Sensitivity Analyses
We examine the robustness of the findings for the primary outcome by performing the following sensitivity analyses
Imputed rho values of 0.2 and 0.8
In the previous analyses for the effect of depression modelling on sucrose preference, we imputed a \(\rho\) value - the imputed within-study correlation between observed effect sizes - of 0.5. Here, we examine the effect of imputing \(\rho\) values of 0.2 and 0.8.
When the \(\rho\) value is assumed to be 0.2, depression modelling had a pooled effect on sucrose preference of SMD = -1.74 (95% CI: -2.53 to -0.96) with a prediction interval of -4.91 to 1.42).
When the \(\rho\) value is assumed to be 0.8, depression modelling had a pooled effect on sucrose preference of SMD = -1.21 (95% CI: -2.15 to -0.28) with a prediction interval of -4.81 to 2.38).
For reference the pooled effect size when rho is assumed to be 0.5 is -1.51 (95% CI: -2.27 to -0.74).
NMD
NMD analysis is not applicable to the analysis of the effects of disease modelling.
2.1.6 Reporting bias/small-study effects
Because of the relationship between SMD effect sizes and variance inherent in their calculation, where study size is small the standard approach to seeking evidence of small-study effects (regression based tests including Egger’s regression test for multilevel meta-analysis) can lead to over-estimation of small-study effect (see for instance 10.7554/eLife.24260). To address this we used Egger’s regression test for multilevel meta-analysis, with regression of SMD effect size against 1/√N, where N is the total number of animals involved in an experiment.
Egger regression based on 117 studies of modelling of depression where sucrose preference was measured showed a coefficient for a small study effect of 2.46 (95% CI: -14.97 to 19.89; p = 0.773).
2.2 Outcome 2: Dopamine concentrations
2.2.1 Risks of bias
Figure 2.2.1 shows the risk of bias traffic light plot for studies investigating the effect of modelling depression on dopamine concentrations in animals. The risk of bias assessment was performed using the SyRCLE RoB tool.
Figure 2.2.1
2.2.2 Reporting completeness
Figure 2.2.2 shows the traffic light plot for reporting completeness summary for studies investigating the effect of the modelling of depression on dopamine concentration in animals. The reporting completeness assessment was performed using the ARRIVE guidelines.
Figure 2.2.2
2.2.3 Meta-analysis
Multilevel analysis is only performed if there are 5 levels or more for at least one of Strain, Study and Experiment, and that is not the case here. 14 experimental comparisons were reported in 4 experiments reported from 4 publications and involving 2 different animal strains. We provide a conventional random effects model to illustrate the data. No subgroup analysis is performed.
2.3 Outcome 3: DOPAC concentration
This was only reported in 2 studies, so no further analysis will be performed.
2.4 Outcome 4: Dopamine / DOPAC ratio
This was only reported in 1 study, so no further analysis will be performed.
2.5 Outcome 5: Dopamine receptor biology
This was only reported in 1 study, so no further analysis will be performed.
3 Dopaminergic agent v Control
25 studies (176 comparisons) investigated the effects of Dopaminergic agents versus Control. The number of studies and individual effect sizes for each outcome were:
Sucrose preference*: 25 studies and 120 comparisons in 10 strains
Dopamine concentration: 3 studies and 27 comparisons in 2 strains
DOPAC concentration: 2 studies and 18 comparisons in 2 strains
DA/DOPC ratio: 1 studies and 9 comparisons in 1 strain
Dopamine receptor biology: 1 studies and 2 comparisons in 1 strain
* This outcomes was identified in the study protocol as primary outcomes of interest.
3.1 Outcome 1: Dopamine
3.1.1 Risks of bias
Figure 3.1.1 shows the risk of bias traffic light plot for studies investigating the effect of administering a dopaminergic agent on Sucrose preference in animals. The risk of bias assessment was performed using the SyRCLE RoB tool.
Figure 3.1.1
3.1.2 Reporting completeness
Figure 3.1.2 shows the reporting completeness traffic light plot for studies investigating the effect of administering a dopaminergic agent on Sucrose preference in animals. The reporting completeness assessment was performed using the ARRIVE guidelines.
Figure 3.1.2
3.1.3 Meta-analysis
The effect of administering a dopaminergic agent on Sucrose preference in animals using SMD as the effect size is shown in Figure 3.1.3. The pooled estimate for SMD across all individual comparisons is displayed as a diamond shape at the bottom of the plot. Dotted lines indicate the prediction interval of the pooled estimate.
Figure 3.1.3
Dopaminergic agents had a pooled effect on Sucrose preference of SMD = 0.75 (95% CI: 0.28 to 1.23 with a prediction interval of -1.44 to 2.95.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0 |
| Study x Strain | 25 | 0.86 |
| Study x Strain x Experiment | 33 | 0.03 |
3.1.4 Subgroup analyses and meta-regressions
For each outcome, the covariates of interest for subgroup analyses and meta-regressions were:
Sex
Method of disease induction
Route of intervention administration
Whether the intervention was prophylactic or therapeutic (i.e. administered before or after disease model induction)
Duration of treatment period
The intervention administered
The efficacy of the drug (i.e. whether the drug is a partial or full agonist)
The selectivity of the drug
Potency of the intervention
Dose of intervention
We also conducted subgroup analyses using (1) SyRCLE Risk of Bias and (2) ARRIVE reporting completeness assessment scores as covariates to evaluate their influence on effect size estimates. These were not specified in the study protocol, but evaluation of risk of bias is required for the Summary of Evidence table, and no studies were considered at low risk of bias or high reporting completeness to allow such a sensitivity analysis
The significance (p value) reported is that for a test of whether the moderators are significantly different one from another, rather than whether the effect is significantly different from 0.
Sex
Figure 3.1.4.1 displays the estimates for the pooled SMD’s when comparisons are stratified by sex of the animal. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by sex, is displayed as a diamond shape at the bottom of the plot.
Figure 3.1.4.1
The p-value for the association between the sex of animal groups used and outcome reported was 0.173.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0 |
| Study x Strain | 25 | 0.877 |
| Study x Strain x Experiment | 33 | 0 |
Category of disease induction
Figure 3.1.4.2 displays the estimates for the pooled SMD’s when comparisons are stratified by the category of disease induction. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by category of disease induction, is displayed as a diamond shape at the bottom of the plot.
Figure 3.1.4.2
The p-value for the association between whether genetic or pharmacological models were used and outcome reported was 0.884.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0 |
| Study x Strain | 25 | 1.089 |
| Study x Strain x Experiment | 33 | 0.029 |
Route of intervention administration
Figure 3.1.4.3 displays the estimates for the pooled SMD’s when comparisons are stratified by the route of intervention administration. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by route of intervention administration, is displayed as a diamond shape at the bottom of the plot.
Figure 3.1.4.3
The p-value for the association between the route of intervention administration and outcome reported was 0.423.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0 |
| Study x Strain | 25 | 0.825 |
| Study x Strain x Experiment | 33 | 0.032 |
Prophylactic or therapeutic intervention
Figure 3.1.4.4 displays the estimates for the pooled SMD’s when comparisons are stratified by whether the intervention was administered prophylactically or therapeutically. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by whether the intervention was administered prophylactically or therapeutically, is displayed as a diamond shape at the bottom of the plot.
Figure 3.1.4.4
The p-value for the association between whether the intervention was administered prophylactically or therapeutically and outcome reported was 0.891.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0 |
| Study x Strain | 25 | 0.912 |
| Study x Strain x Experiment | 33 | 0.033 |
Duration of treatment period
The p-value for the association between whether the intervention was administered prophylactically or therapeutically and outcome reported was 0.149.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0.828 |
| Study x Strain | 25 | 0.437 |
| Study x Strain x Experiment | 33 | 0.034 |
The intervention administered
Figure 3.1.4.5 displays the estimates for the pooled SMD’s when comparisons are stratified by the intervention administered. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by the intervention administered, is displayed as a diamond shape at the bottom of the plot.
Figure 3.1.4.5
The p-value for the association between the intervention and outcome reported was 0.708.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0.856 |
| Study x Strain | 25 | 0.765 |
| Study x Strain x Experiment | 33 | 0.026 |
Dose of intervention
In this iteration of the review, the dopaminergic agents tested against control for their effect on Sucrose preference were: piribedil, aripiprazole, quinpirole, amantadine, buproprion, pramipexole, 2_HBC, L-DOPA, SKF83959, bromocriptine, simvastatin, selegiline, P. orientalis seed, SKF38393, cryptotanshinone, dopamine, ropinirole and tranylcypromine. Meta-regression using the administered dose as an explanatory variable was conducted for each drug where this had been reported in 10 or more experiments from 3 or more publications. Where there are sufficient data, the dashed lines in the plot represents the 95% confidence interval of the regression line and the dotted lines represent the 95% prediction interval. Raw data are plotted with point size adjusted according to effect size precision.
Aripiprazole
The estimate for \(\beta\) was -0.245 (95% CI tp , p = 0.009).
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 4 | 0.233 |
| Study x Strain | 5 | 0 |
| Study x Strain x Experiment | 5 | 0 |
Quinpirole
The estimate for \(\beta\) was 0.001 (95% CI tp , p = 0.249).
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 2 | 0 |
| Study x Strain | 3 | 0.843 |
| Study x Strain x Experiment | 3 | 0.843 |
SyRCLE RoB assessment considered as a categorical variable
Figure 3.1.4.10 displays the estimates for the pooled SMD’s when comparisons are stratified by how many of the SyRCLE risk of bias assessment criteria (of which there are 10) that the experiment met. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by SyRCLE Risk of Bias, is displayed as a diamond shape at the bottom of the plot.
Figure 3.1.4.10
The p-value for the association between SyRCLE Risks of Bias reporting and outcome reported was 0.652.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0 |
| Study x Strain | 25 | 0.906 |
| Study x Strain x Experiment | 33 | 0.034 |
SyRCLE RoB assessment considering those studies where any item is at low risk of bias
Figure 3.1.4.11 displays the estimates for the pooled SMD’s when comparisons are stratified by whether of not any of the SyRCLE Risk of bias domains were rated as low risk of bias. Whiskers indicate the 95% confidence interval of each estimate. The overall pooled SMD, not stratified by SyRCLE Risk of Bias, is displayed as a diamond shape at the bottom of the plot.
Figure 3.1.4.11
The p-value for the association between low SyRCLE Risks of Bias reporting and outcome reported was 0.652.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 10 | 0 |
| Study x Strain | 25 | 0.906 |
| Study x Strain x Experiment | 33 | 0.034 |
ARRIVE reporting guidelines performance
We provide a metaregression where the number of ARRIVE items met is considered as a continuous variable.
Figure 3.1.4.13
The estimate for \(\beta\) was -0.159 (p = 0.146).
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 0 | NA |
| Study x Strain | 0 | NA |
| Study x Strain x Experiment | 0 | NA |
Heterogeneity explained by covariates (Dopaminergic agents and Sucrose preference)
The table below shows which of the covariates, if any, explain some of the heterogeneity observed in the effect sizes of the effect of TAAR1 agonists on Sucrose preference. We present marginal R2, which measures the proportion of variance explained by including moderators in the model (the % change in the between-studies variance when the covariate is included in the model, in other words the % of the heterogeneity explained by the variable). The co-efficients are derived form an RMA model fitted with an intercept (and so represent, for each category, the point estimate and 95% CIs of the effect in that category).
| Moderator | Category | \(\beta\) | 95% CI | Marginal R2 (%) |
|---|---|---|---|---|
| Overall effect | - | 0.752 | 0.277 to 1.227 | - |
| Sex | - | - | - | 5% |
| - | Female | -0.095 | -1.157 to 0.966 | - |
| - | Male | 0.707 | 0.263 to 1.152 | - |
| - | Not reported | NA | NA to NA | - |
| Category of disease model induction | - | - | - | 4.4% |
| - | Behavioural early life stress | 1.001 | -2.57 to 4.571 | - |
| - | Chronic unpredictable mild stress | 0.648 | 0.06 to 1.236 | - |
| - | Genetic models | 1.199 | -2.414 to 4.813 | - |
| - | Pharmacological early life stress | 2.158 | -0.474 to 4.791 | - |
| - | Pharmacological post weaning | 0.53 | -1.147 to 2.207 | - |
| - | Social or social defeat stress | 1.348 | -0.898 to 3.594 | - |
| - | Surgical models | 0.705 | -1.041 to 2.451 | - |
| Administration route | - | - | - | 9.2% |
| - | Intraperitoneal | 0.456 | -0.064 to 0.975 | - |
| - | Oral | 0.762 | 0.184 to 1.341 | - |
| - | Other | 1.24 | 0.116 to 2.365 | - |
| - | Subcutaneous | 1.207 | -0.223 to 2.637 | - |
| Prophylactic or therapeutic intervention | - | - | - | 0.1% |
| - | Prophylactic | 0.726 | 0.104 to 1.348 | - |
| - | Therapeutic | 0.785 | 0.152 to 1.418 | - |
| Duration of treatment period | - | - | - | 11.5% |
| - | 1 to 4 weeks | 0.818 | -0.027 to 1.663 | - |
| - | less than 1 week | 1.069 | -0.293 to 2.432 | - |
| - | 4 weeks or more | 0.056 | -0.868 to 0.979 | - |
| Intervention administered | - | - | - | 15.4% |
| - | 2-HBC | 0.528 | -1.196 to 2.253 | - |
| - | amantadine | -0.112 | -2.131 to 1.907 | - |
| - | aripiprazole | 0.604 | -0.861 to 2.069 | - |
| - | bromocriptine | 0.006 | -1.922 to 1.934 | - |
| - | buproprion | 0.776 | -0.938 to 2.489 | - |
| - | cyrptotanshinone | 0.312 | -2.717 to 3.341 | - |
| - | dopamine | 1.512 | -0.219 to 3.244 | - |
| - | L-DOPA | 0.143 | -1.702 to 1.988 | - |
| - | P.orientalis seed | 2.305 | -0.47 to 5.08 | - |
| - | pramipexole | 0.03 | -2.556 to 2.615 | - |
| - | quinpirole | 0.369 | -1.921 to 2.658 | - |
| - | ropinerole | 0.647 | -0.985 to 2.278 | - |
| - | selegiline | 0.452 | -2.471 to 3.375 | - |
| - | simvastatin | 1.001 | -15.995 to 17.996 | - |
| - | SKF38393 | 0.128 | -1.776 to 2.032 | - |
| - | SKF83959 | 2.631 | 0.31 to 4.951 | - |
| - | tranylcypromine | 1.111 | -1.765 to 3.987 | - |
| Risk of Bias | - | - | - | 1.1% |
| - | 0 criteria met | 0.822 | 0.284 to 1.361 | - |
| - | 1 criteria met | 0.614 | -0.162 to 1.39 | - |
| Reporting completeness | - | - | - | 6.9% |
| - | per unit increase | -0.159 | -0.378 to 0.06 | - |
3.1.5 Sensitivity Analyses
We examine the robustness of the findings for the primary outcome by performing the following sensitivity analyses
Imputed rho values of 0.2 and 0.8
In the previous analyses for the effect of TAAR1 agonists on Sucrose preference, we imputed a \(\rho\) value - the imputed within-study correlation between observed effect sizes - of 0.5. Here, we examine the effect of imputing \(\rho\) values of 0.2 and 0.8.
When the \(\rho\) value is assumed to be 0.2, the TAAR1 interventions had a pooled effect on Sucrose preference of SMD = 0.97 (95% CI: 0.6 to 1.34) with a prediction interval of -0.69 to 2.63).
When the \(\rho\) value is assumed to be 0.8, the TAAR1 interventions had a pooled effect on Sucrose preference of SMD = 0.29 (95% CI: -0.33 to 0.92) with a prediction interval of -2.72 to 3.31).
For reference the pooled effect size when rho is assumed to be 0.5 is 0.75 (95% CI: 0.28 to 1.23).
NMD
For Sucrose preference, an NMD was calculable for 117 out of 120 comparisons, i.e. 97.5 % of comparisons.
The effect of administering a TAAR1 agonist on Sucrose preference in animals using NMD as the effect size is shown in Figure 3.1.5. The pooled estimate for NMD across all individual comparisons is displayed as a diamond shape at the bottom of the plot. Dotted lines indicate the prediction interval of the pooled estimate.
Figure 3.1.5
Dopaminergic interventions had a pooled effect on Sucrose preference of NMD = 68.71 (95% CI: 48.34 to 89.08) with a prediction interval of -27.81 to 165.23). For reference the pooled effect size for SMD was 0.75 (95% CI: 0.28 to 1.23).
117 experimental comparisons were reported in 32 experiments reported from 24 publications and involving 9 different animal strains.
| Level | Number of categories for that level included in this analysis | Attributable variance |
|---|---|---|
| Strain | 9 | 86.94 |
| Study x Strain | 24 | 847.62 |
| Study x Strain x Experiment | 32 | 739.23 |
3.1.6 Reporting bias/small-study effects
Because of the relationship between SMD effect sizes and variance inherent in their calculation, where study size is small the standard approach to seeking evidence of small-study effects (regression based tests including Egger’s regression test for multilevel meta-analysis) can lead to over-estimation of small-study effect (see for instance 10.7554/eLife.24260). To address this we used Egger’s regression test for multilevel meta-analysis, with regression of SMD effect size against 1/√N, where N is the total number of animals involved in an experiment.
Egger regression based on 120 studies of TAAR1 Agonist v Control where Sucrose preference was measured showed a coefficient for a small study effect of 2.12 (95% CI: -12.6 to 16.84; p = 0.768) in the context of a baseline estimate of effect of 0.23 (95% CI: -3.85 to 4.31; p = 0.900).
3.2 Outcome 2: Dopamine concentration
3.2.1 Risks of bias
Figure 3.2.1a shows the risk of bias summary for studies investigating the effect of administering a TAAR1 agonist on Sucrose preference in animals. The risk of bias assessment was performed using the SyRCLE’s RoB tool. Figure 3.2.1b shows the corresponding traffic light plot.
Figure 3.2.1
3.2.2 Reporting completeness
Figure 3.2.2a shows the reporting completeness summary for studies investigating the effect of administering a TAAR1 agonist on Sucrose preference in animals. The reporting completeness assessment was performed using the ARRIVE guidelines. Figure 3.2.2b shows the corresponding traffic light plot.
Figure 3.2.2
3.2.3 Meta-analysis
Multilevel analysis is only performed if there are 5 levels or more for at least one of Strain, Study and Experiment, and that is not the case here. 27 experimental comparisons were reported in 3 experiments reported from 3 publications and involving 2 different animal strains. We provide a conventional random effects model to illustrate the data. No subgroup analysis is performed.
3.3 Outcome 3: DOPAC concentration
This was only reported in 2 studies, so no further analysis will be performed.
3.4 Outcome 4: Dopamine / DOPAC ratio
This was only reported in 1 study, so no further analysis will be performed.
4. Observed relationships between different outcomes measures in the same cohorts of animals
We selected cohorts where at least one outcome was presented for at least two outcome types. Where there were two or more of the same outcome type within a cohort we calculated a standardised mean difference effect size for that outcome in that cohort, along with its standard error. Where there was a single effect size within a cohort we took the standard error of that effect size.
Then, for each pair of outcome measures we plotted the effect sizes for each cohort, and fitted a regression line weighted on the standard error in the outcome measure represented on the x-axis. Outcome measure pairs are coded according to whether they come from model induction studies (red, expectation of worsening anhedonia) or from intervention studies (gree, expecttaion of improvement in anhedonia). The number of experimental comparisons observed from each cohort is reflected in the size of the symbol, and shown in the figure legend.
4.1 Relationship between change in Sucrose preference test and change in measured dopamine concentrations
4.2 Relationship between change in Sucrose preference test and change in measured DOPAC concentrations
4.3 Relationship between change in Sucrose preference test and change in measured dopamine / DOPAC ratio
4.4 Relationship between change in Sucrose preference test and change in dopamine receptor biology
4.5 Relationship between change in dopamine concentrations and change in DOPAC concentrations
4.6 Relationship between change in dopamine concentrations and change in dopamine / DOPAC ratio
4.7 Relationship
between change in dopamine concentrations and change in dopamine
receptor biology
5. Attrition bias and adverse effects of treatment
0% of 1485 animals in Control cohorts and 0% of 1390 animals in Intervention cohorts ‘dropped out’ between allocation to group and outcome measurement. Given that 10 of 186 interventions (5.38%) were administered as a single dose, treatment emergent adverse effects likely to lead to withdrawal of an animal from the study would be unusual, and technical failure or attrition is more likely. This analysis is based on full reporting of animals excluded from analyses, and it may be that group sizes were specified ‘after the event’, or that there was unreported replacement of animals excluded during the experiment, so these data should be interpreted with caution.
6. Summary of the evidence
7. Software used
We used R version 4.3.1 (R Core Team 2023) and the following R packages: devtools v. 2.4.5 (Wickham et al. 2022), dosresmeta v. 2.0.1 (Crippa and Orsini 2016), ggpubr v. 0.6.0 (Kassambara 2023), gtools v. 3.9.4 (Bolker, Warnes, and Lumley 2022), Hmisc v. 5.1.1 (Harrell Jr 2023a), kableExtra v. 1.3.9.9001 (Zhu 2023), knitr v. 1.45 (Xie 2014, 2015, 2023), Matrix v. 1.6.1.1 (Bates, Maechler, and Jagan 2023), meta v. 6.5.0 (Balduzzi, Rücker, and Schwarzer 2019), metadat v. 1.2.0 (White et al. 2022), metafor v. 4.4.0 (Viechtbauer 2010), mvmeta v. 1.0.3 (Gasparrini, Armstrong, and Kenward 2012), numDeriv v. 2016.8.1.1 (Gilbert and Varadhan 2019), orchaRd v. 2.0 (Nakagawa et al. 2023), patchwork v. 1.1.3 (Pedersen 2023), PRISMA2020 v. 1.1.1 (Haddaway et al. 2022), rje v. 1.12.1 (Evans 2022), rms v. 6.7.1 (Harrell Jr 2023b), robvis v. 0.3.0.900 (McGuinness and Higgins 2020), tidyverse v. 2.0.0 (Wickham et al. 2019), usethis v. 2.2.2 (Wickham et al. 2023), xtable v. 1.8.4 (Dahl et al. 2019).
SMD_S_cog_CatDisInd[SMD_S_cog_CatDisInd$CategoryDiseaseInduction == “Genetic”][[“k”]]